Why Are Smartwatches Focusing on Notifications?

It is very interesting to see the new smartwatches focusing on notifications as their main feature. This begs the question; why are notifications so important?

Are notifications so important that many people are willing to purchase a several hundred dollar device and wear it wherever they go?

I don’t think so. I think that the only reason why smartwatches are offering notifications is because it was relatively easy to do. Smartwatches are small so you can’t display a lot of information on them. You can’t provide a good UI that can be used to enter information. The only use-case that was left was notifications. The focus on notifications was not because notifications are important; it was because there was nothing else that Samsung, Google could think of putting on the device.

So the issue remains. Smartwatches are a form-factor in search of a use-case. This is not innovation.

Innovation in wearables lies in understanding what problem they can uniquely solve. How can a device that will be with you at all times enrich your life?

Of course, there may not be a market for wearables after all. Unlike smartphones, wearables are not a replacement for a device that people were already carrying around with them. Wearables are asking the public to carry a second device in addition to their smartphone, which overlaps a lot in functionality. Whether or not there is a market for such a device is very unclear. Even if it existed, it is easy to imagine that it would take a huge amount of time to spread. It is a speculative market.

Innovation is rarely about a technology searching for a market. It’s more often about making a complex product simpler and easier to use, thereby both increasing the number of people who use it and the occasions in which it is used. Notifications simply don’t qualify for this.

Why the Fallacy of Android-First

Dave Feldman wrote a very interesting post on TechCruch (“The Fallacy of Android-First”) where he details why the startup that he founded (Emu) launched Android-first, but after sixteen months, they reverted to iOS only.

There are many interesting points in this post. Here, I would like to categorize his findings and to draw a typical general picture of an innovative market leader and a follower frantically trying to catch up.

The allure of Android

Followers generally try to catch up with the combination of a) price and b) more features. With both more features and a price benefit, it seemly looks like the follower’s offering is better in all accounts. However, if you look under the hood, you often find that the features haven’t been well thought out and that they are actually quite useless.

In comparison, leaders usually focus on actual benefits. If they succeed, the leaders prevail and the market separates into low-end which becomes a price war, and the high-end which is rather stable. If leaders fail and are dragged into the price war, then the market loses the leader and everybody chases features that look good on paper, but are not beneficial to the user.

This is a common theme in many markets. It is also what is happening in mobile.

The Dave’s article, he mentions the allure of Android as the following;

  1. On Android, you can replace the built-in Messages app, while still using the underlying SMS/MMS medium, saving the effort of building a communication service.
  2. Android apps were supposedly easier to build.
  3. Fragmentation was supposedly becoming less of an issue.

The reality

The reality was that allure #1 was a feature that was not well implemented. It was so bad that it was close to unusable from a developer point of view.

  1. Android’s SMS APIs are not well documented. The APIs have also changed over time.
  2. Individual apps can block each other from receiving SMSes. This means that the presence of other apps affects whether your app works or not.
  3. Other issues with MMS make it a nightmare to support.

So the feature was there on Android, but it was very difficult to use in the real world.

There are also other issues described in the post and they basically say the same thing; Android has the features and support, but it’s often not very useful.

The lesson

The lesson is that features which the followers implement are rarely useful. You can’t trust them to have thought out all the issues. Although leaders will also fail sometimes, followers are much more likely to introduce useless features.

How are Apps Dominating Mobile Usage?

On April 1st, 2014, analytics firm Flurry released a report on how time is spent on mobile devices.

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This data is interesting for a number of reasons;

  1. Apps are dominating the mobile usage. As of 2014, Internet browsers are used for only 14% of the time. 86% of the time, mobile users are using apps.
  2. App dominance is increasing. In 2013, Internet browsers were used for 20% of the time compared to 14% in 2014.
  3. Facebook and other social activities constitute 28% of usage time. This compares to 32% for gaming.
  4. Other usages are fragmented with 4% for YouTube (watching video), 4% for productivity, 3% for news.

What does this all mean? Here are a few thoughts of mine.

Why did apps dominate mobile usage?

Both mobile apps and the mobile web have their pros and cons. Although it’s easy to point out the advantages that apps have and to attribute success to these, we have to remember that a lot of people predicted that HTML5 would ultimately win. There are arguments for both sides and hence it’s very difficult to understand what the ultimate driver of success was.

Why is this important? Why do we have to analyze what has already happened?

I have a sense that the success of apps on mobile might affect how we use desktop computers. It is not entirely unthinkable that we might see a resurgence of apps on the desktop. By analyzing how apps dominated mobile usage, we might gain insight on whether this is truly likely.

How can Microsoft fix the ecosystem gap

The smartphone market is dominated by Android and iPhone and it is increasing difficult for new entrants to gain a foothold in the market. Windows Phone is reported to be gaining market share in the low-end, but we want to know whether it can possibly grow to be a significant player.

The problem is the ecosystem. Android and iPhone both have a large number of apps and services. Windows Phone lags in this regard and this is considered the reason why it doesn’t stand a chance.

Let’s look at this by category. Looking a social networks, the big ones are cross platform. Facebook, WhatsApp, LINE, Instagram, Pinterest and many others have native apps for Windows phone. Windows Phone no longer lags here.

In games, Windows Phone lags a lot. Popular games like Puzzle & Dragons and Candy Crush Saga are not yet available.

In the other categories, it is possible that Windows Phone still is vastly inferior in the number of apps available. However, this probably is not very much of an issue. They aren’t an vital part of the smartphone experience.

If Microsoft can convince major game developers to create Windows Phone versions, then it can mostly fix the platform gap.

Usage itself is different from desktops

Although I don’t have data available for desktop computers, I imagine that it would be very different from Flurry’s data. Instead of games, we would see a lot of productivity apps (mostly MS-Office) being used. Email applications would also be huge.

It’s not a simple case of apps replacing the web. It’s that these devices are fulfilling a different purpose. Hence there is no guarantee that companies with a big presence on the desktop web will ultimately succeed on mobile.

For example, Gmail has a large presence on the desktop web and is also included in Android as a part of Google Play. It maintains a large market share of email on mobile devices. It doesn’t really matter though because the preferred messaging tool on mobile is not email. Instead, the social messaging platforms dominate.

Likewise, Google maintains a large market share for mobile web search. It doesn’t matter because people don’t do web search on their mobile devices.

Will Google Use Humans to Fix Google Now?

I have never used Google Now, but I was always skeptical. The use cases that were being reported on the web always were extremely limited, and it seemed that they were simply telling us about the things that worked but not about the things that didn’t.

A couple of days ago, Janko Roettgers wrote on GigaOM about how Google Now actually fails, even in the limited tasks it’s supposed to be good at.

We often assume that because Google is collecting huge amounts of information about their users, they are able to understand a lot about who we are and what we want to do. Yes, Google does know where you live and it knows exactly what keywords you used on your searches yesterday. It knows exactly where you are right now. This is all very creepy, especially if you are an Android user. The problem is, there is no guarantee that this information will let Google know your current intentions with any accuracy.

Google has been described as a “decade-old machine learning project”. There are two products from Google which have shown how this can actually be turned into something useful. They are Google AdSense and Google Maps.

Google search basically selects the ads (AdWords) to be displayed based on the keywords that were entered in the search field. Although the information that Google holds about the user is also used to tweak the results, this is not the main driver of the AdWord ads to be displayed. With AdWords, the user has directly expressed their intent through the search keywords and Google does not try to second-guess it. This intent is what drives the ads and this is why I don’t include it in the current discussion.

AdSense is more “intelligent” than AdWords because it tries to guess user intent. It analyses the content of the page the user currently is browsing. It uses knowledge of what pages the user has visited recently. It uses location data. It combines all of these to determine which ad the user is most likely to click on. In reality, AdSense fails most of the time. It does not correctly estimate the user’s current intent. But that’s OK. The click-through rate (CTR) of AdSense is at most a few percent and the vast majority of people aren’t interested in what is shown in an online ad. It’s completely acceptable for AdSense to get it wrong most of the time. Therefore, the “intelligent” guesses of AdSense are successful even if they are completely wrong most of the time. AdSense will still be immensely successful when the majority of users are pissed-off by the ads. It only takes a small percentage of correct answers to succeed.

Google Maps is a totally different kind of “intelligence”. Google Maps has to be accurate for the vast majority of the time. It has to be something like 99.999% accurate or more. Otherwise, we would constantly get reports that some poor drivers drove themselves into a desert. How can Google Maps be so accurate when AsSense is so sloppy? The secret lies in humans. To quote an article by Alexis Madrigal on The Atlantic.

I came away convinced that the geographic data Google has assembled is not likely to be matched by any other company. The secret to this success isn’t, as you might expect, Google’s facility with data, but rather its willingness to commit humans to combining and cleaning data about the physical world. Google’s map offerings build in the human intelligence on the front end, and that’s what allows its computers to tell you the best route from San Francisco to Boston.

Even though Google gets vast amounts of information from satellites and street-view cars, it has to combine these with an army of human beings to gain accuracy. Without these human beings, they cannot get the error rate to an acceptable level. The kind of “intelligence” in Google Maps can only be attained with a huge number of people who manually curate the information.

Now let’s get back to Google Now. Which kind of “intelligence” do we need? Do we want a personal assistant that thinks it is acceptable to guess correctly only a few percent of the time? Or do we want a personal assistant that truly knows what we want to do next?

If we want the latter, we may have to be content with an army of human beings plowing through your most personal information, helping Google’s not-so-accurate machine learning algorithms to make sense of your daily routines.